dc.contributor.author
Tomasello, Rosario
dc.contributor.author
Garagnani, Max
dc.contributor.author
Wennekers, Thomas
dc.contributor.author
Pulvermüller, Friedemann
dc.date.accessioned
2018-08-06T06:00:11Z
dc.date.available
2018-08-06T06:00:11Z
dc.identifier.uri
https://refubium.fu-berlin.de/handle/fub188/22625
dc.identifier.uri
http://dx.doi.org/10.17169/refubium-426
dc.description.abstract
Neuroimaging and patient studies show that different areas of cortex respectively specialize for general and selective, or category-specific, semantic processing. Why are there both semantic hubs and category-specificity, and how come that they emerge in different cortical regions? Can the activation time-course of these areas be predicted and explained by brain-like network models? In this present work, we extend a neurocomputational model of human cortical function to simulate the time-course of cortical processes of understanding meaningful concrete words. The model implements frontal and temporal cortical areas for language, perception, and action along with their connectivity. It uses Hebbian learning to semantically ground words in aspects of their referential object- and action-related meaning. Compared with earlier proposals, the present model incorporates additional neuroanatomical links supported by connectivity studies and downscaled synaptic weights in order to control for functional between-area differences purely due to the number of in- or output links of an area. We show that learning of semantic relationships between words and the objects and actions these symbols are used to speak about, leads to the formation of distributed circuits, which all include neuronal material in connector hub areas bridging between sensory and motor cortical systems. Therefore, these connector hub areas acquire a role as semantic hubs. By differentially reaching into motor or visual areas, the cortical distributions of the emergent ‘semantic circuits’ reflect aspects of the represented symbols’ meaning, thus explaining category-specificity. The improved connectivity structure of our model entails a degree of category-specificity even in the ‘semantic hubs’ of the model. The relative time-course of activation of these areas is typically fast and near-simultaneous, with semantic hubs central to the network structure activating before modality-preferential areas carrying semantic information.
en
dc.format.extent
19 Seiten
de
dc.rights.uri
https://creativecommons.org/licenses/by/4.0/
de
dc.subject
Word acquisition
en
dc.subject
semantic grounding
en
dc.subject
Hebbian cell assembly
en
dc.subject
Biologically inspired neural network
en
dc.subject
Word recognition EEG-MEG responses
en
dc.subject
Cortical connectivity
en
dc.subject.ddc
100 Philosophie und Psychologie::150 Psychologie::153 Kognitive Prozesse, Intelligenz
de
dc.subject.ddc
100 Philosophie und Psychologie::150 Psychologie::152 Sinneswahrnehmung, Bewegung, Emotionen, Triebe
de
dc.title
Brain connections of words, perceptions and actions: A neurobiological model of spatio-temporal semantic activation in the human cortex
de
dc.type
Wissenschaftlicher Artikel
de
dcterms.bibliographicCitation.doi
10.1016/j.neuropsychologia.2016.07.004
dcterms.bibliographicCitation.journaltitle
Neuropsychologia
dcterms.bibliographicCitation.pagestart
111
dcterms.bibliographicCitation.pageend
129
dcterms.bibliographicCitation.volume
98
dcterms.bibliographicCitation.url
https://doi.org/10.1016/j.neuropsychologia.2016.07.004
de
refubium.affiliation
Philosophie und Geisteswissenschaften
de
refubium.affiliation.other
Brain Language Laboratory
de
refubium.resourceType.isindependentpub
no
de
dcterms.accessRights.openaire
open access
dcterms.isPartOf.issn
1873-3514
dcterms.isPartOf.issn
0028-3932